Research on enhancing UAV photogrammetry for efficient flood prevention riprap volume estimation

Accurate estimation of flood-control rock stockpiles is crucial for effective flood prevention and disaster management. Traditional surveying methods are labor-intensive, time-consuming, and carry safety risks. This study presents an advanced UAV-based photogrammetry approach for efficient and precise estimation of flood-control rock volumes. By integrating structure from motion and multi-view stereo technologies, the method generates high-resolution 3D models and calculates volumes using digital elevation model differencing. The approach addresses key challenges, such as irregular stockpile shapes, concealed bases, and rough surfaces, offering enhanced accuracy. Field experiments in Jiangsu Province validate the method, with a volume estimation error of only 0.61%. Compared to traditional methods, the UAV technique increases data collection efficiency by 3 to 5 times, significantly reducing labor and operational costs. This research not only advances the application of UAV photogrammetry in flood-control material management but also contributes to the development of intelligent, automated systems for rapid emergency response and resource monitoring in flood-prone areas. The proposed method represents a significant improvement in the digital management of flood-control reserves, offering an effective tool for optimizing disaster preparedness and response strategies.